The present disclosure relates to an apparatus for recognizing an iris and an operating method thereof, and particularly, to an apparatus for recognizing an iris and an operation method thereof capable of efficiently and effectively recognizing the iris in acquired iris images.
In many cases, electronic products such as computers and mobile phones include the personal information of a user. Recently, electronic commerce using this personal information tends to be widely spread. Accordingly, these devices need to ensure the personal information. It can only be accessed by the original user and they are required to accurately identify a user. To this end, ID and password are commonly used by people. However, such a scheme has limitations with respect to personal information protection and anti-hacking. So various alternatives have been proposed to overcome these issues.
As one of them, many kinds of biometric technologies are being gradually commercialized. Biometric technologies are used to identify users based on biological and behavioral characteristics. In particular, fingerprint recognition technology has been incorporated to some mobile phones. They are popular and widely used. However, easy spoofing of fingerprint may threaten the data security of personal information. Thus, an apparatus for recognizing iris has received attention as an alternative method of addressing such limitation.
Iris recognition technology uses the pattern on the iris of a person's eye to check the identity of the person. It has an advantage over fingerprint in that it is more difficult to spoof.
As well, high security can be achieved using highly accurate iris recognition technology. By the way, the accuracy of iris recognition technology is highly dependent on the inherent iris image quality. One of most important quality factors of iris image is focus. So it is critical to assess the focus quality to achieve high accuracy of iris recognition.
Several known techniques have been used for the assessment of image focus quality. They are based on wavelet, convolution kernel, sobel edge and image variance. However, some of these techniques have difficulty in accurately assessing the focus quality of the iris image and have high computational complexity. Some of them are not robust to image brightness or the size of iris in an image, which results in difficulty in assessing the focus quality accurately. They assess the entire image or fixed partial areas in the image, which in turn may affect the accuracy of focus assessment for the iris in the image because other objects such as eyeglasses frame, eyebrow or eyelashes in the image may have an impact on the focus assessment. When the imaging target is an iris, for the purpose of iris recognition, it is important that iris recognition systems should be designed to check if the iris in the image is in good focus.